Session Program

Abstract - -- This paper presents fuzzy similarity based Fuzzy Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) for z-numbers. The classical fuzzy TOPSIS techniques use closeness coefficient to determine the rank order by calculating Fuzzy Positive Ideal Solution (FPIS) and Fuzzy Negative Ideal Solution (FNIS) simultaneously. The authors propose fuzzy similarity to replace closeness coefficient by doing ranking evaluation. Fuzzy similarity is used to calculate the similarity between two fuzzy ratings (FPIS and FNIS). Fuzziness is not sufficient enough when dealing with real information and a degree of reliability of the information is very critical. Hence, the implementation of z-numbers is taken into consideration as they can capture better the knowledge of human being and are extensively used in uncertain information development to deal with linguistic decision making problems. A numerical example is given to illustrate the application of the proposed technique in ranking company performance assessment. The results show that it is highly feasible to use the proposed technique in performance assessment.

Abstract - Cloud computing technology (CCT) provides virtual services accessible to its users from anywhere based on subscriptions with attractive costs wherever they are. It also brings many different benefits to businesses as well as the public by saving them time and resources that would be needed for establishing and operating their own Information Technology infrastructure. For this reason, the objectives of this study are to identify important decision criteria and sub criteria that are relevant to the CCT selection problem; to provide an effective framework to evaluate and select the most appropriate CCT and to apply proposed approach through an empirical study. Technology selection in general is a complicated multi-criteria problem that concerns both quantitative and qualitative parameters, which are usually conflicting and uncertain. Interval Valued Intuitionistic Fuzzy (IVIF) set is a powerful method to cope with uncertainty by taking both degree of membership and nonmembership function in an interval. Therefore, a multi-criteria analysis and solution methodology is presented, which incorporates decision makers' insufficient knowledge and other pressures involved in the evaluation with the help of an extension of MULTIMOORA (Multi-objective Optimization by Ratio Analysis plus the Full Multiplicative Form) technique in order to rank alternatives for handling imprecise data in selecting the most suitable CCT. To demonstrate the usability of the proposed technique, an illustrative study is also given.

Abstract - Cloud computing promises enhanced scalability, flexibility, and cost-efficiency. In practice, however, there are many uncertainties about the usage of cloud computing resources in the e-commerce context. As e-commerce is dependent on a reliable and secure online store, it is important for decision makers to adopt an optimal cloud computing mode (Such as SaaS, PaaS and IaaS). This study assesses the factors associated with cloud-based e-commerce based on TOE (technological, organizational, and environmental) framework using multicriteria decision-making technique (Fuzzy TOPSIS). The results show that Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) approach proposes software-as-a-service (SaaS) as the best choice for e-commerce business.

Abstract - Personnel selection constitutes an important decision making problem that determines, to a large degree, the competitiveness and performance of organizations. The personnel selection process works with the vacancy requirements and the available information concerning to the applicants. Complicating this process, we have diverse competencies or skills to evaluate the candidates for a vacancy, which can be modeled as a multicriteria problem. In this article, we propose a multicriteria approach to solve instances of personnel selection problem. For that, we use a software called SADGAGE, which solves instances of the multicriteria ranking problem with decreasing preferences direction about the preferences of a decision maker.

Abstract - Everyone knows that technology altered profoundly the way we communicate and interact with the world, from personal computers to mobile devices. The impact of emerging new technologies affects every industry, and supply chain or logistics are no exception. Digital Supply Chain (DSC) create added various benefits to companies, financial or otherwise. Today, an emerging trend in supply chain management worldwide is a movement of the focus from that of classical supply chain to that of DSC. Modern organizations therefore shall interact with their dealers through DSC processes for production and delivery operations of goods and services. Due to its multi criteria nature, this study proposes a novel approach to evaluate supplier selection process under DSC environment for group decision making in an uncertain environment. The proposed framework combines for the first time the Interval Valued Intuitionistic Fuzzy (IVIF) Analytic Hierarchy Process (AHP) to evaluate criteria weights and IVIF Additive Ratio Assessment (ARAS) methodology for alternative assessment procedure. The paper also analyzes the selection of a suitable supplier in a real case study from Turkey to demonstrate the validity of the proposed approach.

Abstract - This exploratory study attempts to prove the premise that performance measurements are instrumental in the often inconsistent and dynamic supplier selection problem. The fundamental Supply Chain Management (SCM) phases of Plan, Source, Make, and Deliver and at what level of managerial decision making (Operational, Tactical or Strategic) are the performance measures considered in supplier selection and potential buyer-supplier partnerships. Utilizing survey responses, the scores of over 400 buyers comparing seven suppliers in a competitive, electronics industry were consolidated across the four phases of SCM then within each phase, the responses and scores were again mapped into the level of decision making involved. Fuzzy probabilities of fit into intervals for the average scores were determined and goals based on beliefs attributed to the goals were set. Results confirmed that the Source phase was most important to buyers followed by the Plan phase. The level of decision making was highlighted as Tactical.